Thoughtworks Technology Podcast

How fitness functions can help us govern and measure AI

26 snips
Mar 6, 2025
Rebecca Parsons, former CTO emerita of ThoughtWorks and co-author of 'Building Evolutionary Architectures', joins Neal Ford, a regular host and also co-author, to dive into the dynamic world of AI governance. They explore how fitness functions can optimize AI performance, ensuring systems meet their intended goals. The duo discusses identifying biases within AI, the importance of operationalizing large language models, and the need for objective metrics in rapidly changing tech landscapes. Their insights reveal how adaptability can shape the future of AI.
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INSIGHT

Defining 'Good' with Fitness Functions

  • Fitness functions measure how well a solution fulfills its goals, like minimizing distance in the traveling salesman problem.
  • They help balance competing goals, like throughput and variety on a production line, by defining 'good'.
INSIGHT

Capabilities vs. Behavior

  • Fitness functions test a system's capabilities ('ilities'), like scalability or elasticity, not its domain behavior.
  • This complements traditional testing by focusing on architectural characteristics.
ADVICE

Guiding AI Evolution

  • Define the desired capabilities of your AI system, like acceptable latency.
  • Build fitness functions around these capabilities to guide evolution and enable quick adaptation to new models or vendors.
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